Training medical students in health promotion: twenty years of experience at the Faculty of Medicine of the University of Geneva
Bibliographic record
Abstract
Background: In most cases, the work of medical doctors, be they general practitioners or specialists, involves some dimension of health promotion (HP). There is thus ample justification for increasing the awareness of medical students vis-à-vis HP and its relevance for their future practice.Methods: In the context of a major curriculum reform (problem-based learning [PBL]) at the Faculty of Medicine of the University of Geneva in the mid-1990s, several steps were taken to strengthen HP throughout the curriculum and include HP in its key domains as defined by the Ottawa Charter (OC).Results: First, the political dimension of HP was developed in a series of first- and fifth-year lectures and third-year workshops; second, community action was strengthened through a third year one-month community immersion program; third, the development of personal skills was integrated into second- and third-year PBL cases and into fourth-and fifth-year learning activities in clinical settings as well as second- and third-year HP electives; in terms of reorienting health services, the chosen approach included the development of a HP-specific track in the context of a Certificate of Advanced Studies (CAS) in Community Health and a Master of Advanced Studies(MAS) in Public Health. Furthermore, a supportive intra-university environment was created through a collaborative convention with Health Promotion Switzerland, which is in charge of coordinating HP in Switzerland.Conclusion: In our view, HP teaching for medical students seems all the more relevant given that future medical doctors will have to take care of an increasing number of patients likely to develop chronic non-communicable diseases.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".